Nonetheless, no matter how mature a company is, there will always be a need to perform reactive data quality maintenance tasks. Again, it is about data adequacy to a business need, not perfect data. Data correction projects must have clearly established requirements, objectives, and metrics to measure success. Furthermore, every data issue has a root cause. When correcting existing data issues, make sure to identify why and how the issue occurred and implement corrective actions to prevent similar anomalies in the future.
Research the best way to log analyses, causes, and proposed resolutions
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